Abstract
This paper presents an and-sway control for overhead cranes with load hosting. The overhead crane involves a planar motion in conjunction with a hosting motion. In order to reduce the sway of the load after positioning, we design the trajectory for the position of the trolley. Radial basis function networks (RBFNs) are employed to generate the desired trolley position, and then a particle swarm optimization (PSO) is used for the learning algorithm, in which the maximum swing angle after positioning is adopted as the objective function. The ability of the proposed anti-sway control is confirmed by numerical simulation.
